In the world of baseball, there is very little film or ‘Eye test’ versus statistics debate any longer. Sure, one of the older guys may get upset and write a foot stomping column once a year, but for the most part, anyone who is regarded seriously in baseball media (and especially fantasy baseball) plays solely in the realm of advanced statistics. If you have an argument to make, it needs to be evidence based.
One of the reasons they are able to do this and we aren’t in football is simple: baseball is a game of one on one interactions. Pitcher/Batter confrontations are very different than 22 players on a football field all acting independently of one another; but I still believe that there is a lesson to be learned from the field of baseball that hasn’t been explored fully. Namely, the concept of rate statistics. Essentially, rather than measuring the volume of something, rate statistics measure how often it occurs, compares that to league average and is able to tell you if a player is getting ‘lucky’ or not performing at their true skill level. For context, see the SaberMetric Library at Fangraphs. This definition of xFIP will help explain the concept.
There is a lot of data mining that will have to be done in order to identify any predictive rate statistics for football players. We know that there is little year to year correlation for stats like yards per carry, so in order to find predictive metrics, it’s going to require a lot of research. Wide receivers are of the most interest to me, because predicting their break outs and declines has the largest profit potential in all of fantasy football. What follows is my first foray in attempting to discover if redzone conversion rates are predictable and if there is even a ‘mean’ for a player to regress too.
2013 RZ Performance
|Player||T||C||Yds||RZ TD %||TD|
- That was every player with 10 or more redzone targets in 2013, sorted by conversion rate. The league average on those targets was a 25% conversion rate. I opted to leave out players with less than 10 targets to eliminate some of those noise inherent in this sample. Chances are, if you didn’t receive 10 RZ targets, you likely were not very fantasy relevant.
- Holy crap, Dez Bryant. Not that it’s surprising given his skill set but if you want to make an argument for him as your #1 fantasy WR in that Linehan offense (as discussed here), then I wouldn’t fight you.
- The RV crew is understandably low on Antonio Brown from a dynasty perspective and his .04% RZ conversion rate would explain why.
- Among the notables who were below league average: AJ Green, Deandre Hopkins, Josh Gordon, Mike Floyd, T.Y Hilton, Alshon Jeffery, Randall Cobb and Kendall Wright.
- This is, I think, where the potential of rate statistics comes into play. The next step in this study will be looking at RZTD% by height and over a multi-year strech, to determine if there is an average that players of a certain height or weight tend to play towards in order to predict positive or negative regression. For example, one would expect Alshon Jeffery, a physically imposing player with a solid RZTD% in college to bounce back in the redzone whereas Antonio Brown has never converted a large number of RZ looks into touchdowns.
Look out for more work on this area coming very soon. If you have any ideas on the project, or think I’m terribly misguided, please let me know on Twitter @DavisMattek.